The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD 

## [1] "2020-06-02"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide 

## [1] "6378238 (up from 6265852 yesterday: 1.79 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "380250 (up from 375543 yesterday: 1.25 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 5.96



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1831821 20801 1.15 106180 1031 0.98 5.80
Brazil 555383 28936 5.50 31199 1262 4.22 5.62
Russia 423186 8858 2.14 5031 182 3.75 1.19
United Kingdom 279392 1656 0.60 39452 325 0.83 14.12
Spain 239932 294 0.12 27127 0 0.00 11.31
Italy 233515 318 0.14 33530 55 0.16 14.36
India 207191 8821 4.45 5829 221 3.94 2.81
France 188450 -898 -0.47 28943 107 0.37 15.36
Germany 183879 285 0.16 8563 8 0.09 4.66
Peru 170039 0 0.00 4634 0 0.00 2.73
Turkey 165555 786 0.48 4585 22 0.48 2.77
Iran 157562 3117 2.02 7942 64 0.81 5.04
Chile 108686 3528 3.35 1188 75 6.74 1.09
Mexico 97326 3891 4.16 10637 470 4.62 10.93
Canada 93960 672 0.72 7477 73 0.99 7.96
Saudi Arabia 89011 1869 2.14 549 24 4.57 0.62
China 84161 7 0.01 4638 0 0.00 5.51
Pakistan 76398 3938 5.43 1621 78 5.06 2.12
Qatar 60259 1826 3.12 43 3 7.50 0.07
Belgium 58615 98 0.17 9505 19 0.20 16.22
Bangladesh 52445 2911 5.88 709 37 5.51 1.35
Netherlands 46852 103 0.22 5986 5 0.08 12.78
Belarus 44255 852 1.96 243 3 1.25 0.55
Ecuador 40414 1316 3.37 3438 80 2.38 8.51
Sweden 38589 775 2.05 4468 65 1.48 11.58
Singapore 35836 544 1.54 24 0 0.00 0.07
South Africa 35812 1455 4.23 755 50 7.09 2.11
United Arab Emirates 35788 596 1.69 269 3 1.13 0.75
Portugal 32895 195 0.60 1436 12 0.84 4.37
Switzerland 30874 3 0.01 1920 0 0.00 6.22
Colombia 30593 1209 4.11 1014 51 5.30 3.31
Kuwait 28649 887 3.20 226 6 2.73 0.79
Indonesia 27549 609 2.26 1663 22 1.34 6.04
Egypt 27536 1152 4.37 1052 47 4.68 3.82
Ireland 25066 4 0.02 1658 8 0.48 6.61
Ukraine 24895 333 1.36 733 9 1.24 2.94
Poland 24395 230 0.95 1092 18 1.68 4.48
Romania 19517 119 0.61 1288 12 0.94 6.60
Philippines 18997 359 1.93 966 6 0.62 5.09
Argentina 18319 904 5.19 569 13 2.34 3.11
Dominican Republic 17752 180 1.02 515 13 2.59 2.90
Israel 17285 116 0.68 290 5 1.75 1.68
Japan 16837 50 0.30 902 3 0.33 5.36
Austria 16759 26 0.16 669 1 0.15 3.99
Afghanistan 16509 759 4.82 270 5 1.89 1.64
Panama 14095 258 1.86 352 8 2.33 2.50
Oman 12799 576 4.71 59 9 18.00 0.46
Bahrain 12311 440 3.71 19 0 0.00 0.15
Denmark 11934 35 0.29 580 4 0.69 4.86
Korea, South 11590 49 0.42 273 1 0.37 2.36
Kazakhstan 11571 263 2.33 44 3 7.32 0.38
Serbia 11454 24 0.21 245 1 0.41 2.14
Bolivia 10991 460 4.37 376 33 9.62 3.42
Nigeria 10819 241 2.28 314 15 5.02 2.90
Armenia 10009 517 5.45 158 19 13.67 1.58
Algeria 9626 113 1.19 667 6 0.91 6.93
Czechia 9364 62 0.67 323 2 0.62 3.45
Moldova 8548 188 2.25 307 2 0.66 3.59
Norway 8455 9 0.11 237 1 0.42 2.80
Ghana 8297 227 2.81 38 2 5.56 0.46
Malaysia 7877 20 0.25 115 0 0.00 1.46
Morocco 7866 33 0.42 206 1 0.49 2.62
Iraq 7387 519 7.56 235 20 9.30 3.18
Australia 7229 8 0.11 102 0 0.00 1.41
Finland 6887 2 0.03 320 2 0.63 4.65
Cameroon 6585 188 2.94 200 1 0.50 3.04
Azerbaijan 5935 273 4.82 71 3 4.41 1.20
Guatemala 5586 250 4.69 123 7 6.03 2.20
Honduras 5527 165 3.08 225 8 3.69 4.07
Sudan 5310 137 2.65 307 9 3.02 5.78
Tajikistan 4100 87 2.17 47 0 0.00 1.15
Luxembourg 4020 1 0.02 110 0 0.00 2.74
Hungary 3921 29 0.75 532 5 0.95 13.57
Guinea 3886 42 1.09 23 0 0.00 0.59
Senegal 3836 97 2.59 43 1 2.38 1.12
Djibouti 3779 210 5.88 25 1 4.17 0.66
Uzbekistan 3760 58 1.57 15 0 0.00 0.40
Congo (Kinshasa) 3326 131 4.10 72 0 0.00 2.16
Thailand 3083 1 0.03 58 1 1.75 1.88
Cote d’Ivoire 3024 73 2.47 33 0 0.00 1.09
Greece 2937 19 0.65 179 0 0.00 6.09
Gabon 2803 148 5.57 20 3 17.65 0.71
El Salvador 2653 71 2.75 49 3 6.52 1.85
Bulgaria 2538 19 0.75 144 4 2.86 5.67
Bosnia and Herzegovina 2535 11 0.44 157 3 1.95 6.19
North Macedonia 2391 76 3.28 141 1 0.71 5.90
Croatia 2246 0 0.00 103 0 0.00 4.59
Haiti 2226 0 0.00 45 0 0.00 2.02
Nepal 2099 288 15.90 8 0 0.00 0.38
Kenya 2093 72 3.56 71 2 2.90 3.39
Cuba 2092 9 0.43 83 0 0.00 3.97
Somalia 2089 66 3.26 79 0 0.00 3.78
Estonia 1870 0 0.00 68 0 0.00 3.64
Kyrgyzstan 1845 28 1.54 17 1 6.25 0.92
Maldives 1841 12 0.66 7 1 16.67 0.38
Venezuela 1819 157 9.45 18 1 5.88 0.99
Iceland 1806 0 0.00 10 0 0.00 0.55
Sri Lanka 1683 40 2.43 11 0 0.00 0.65
Lithuania 1682 4 0.24 71 1 1.43 4.22
Slovakia 1522 0 0.00 28 0 0.00 1.84
New Zealand 1504 0 0.00 22 0 0.00 1.46
Slovenia 1475 2 0.14 109 0 0.00 7.39
Mali 1351 36 2.74 78 0 0.00 5.77
Ethiopia 1344 87 6.92 14 2 16.67 1.04
Guinea-Bissau 1339 0 0.00 8 0 0.00 0.60
Equatorial Guinea 1306 0 0.00 12 0 0.00 0.92
Lebanon 1242 9 0.73 27 0 0.00 2.17
Albania 1164 21 1.84 33 0 0.00 2.84
Nicaragua 1118 359 47.30 46 11 31.43 4.11
Costa Rica 1105 21 1.94 10 0 0.00 0.90
Zambia 1089 0 0.00 7 0 0.00 0.64
Tunisia 1086 2 0.18 48 0 0.00 4.42
Latvia 1071 5 0.47 24 0 0.00 2.24
Central African Republic 1069 0 0.00 4 0 0.00 0.37
Kosovo 1064 0 0.00 30 0 0.00 2.82
Paraguay 1013 18 1.81 11 0 0.00 1.09

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 373040 1329 0.36 29968 51 0.17 8.03 19175.92 1540.49 1 in 52
New Jersey 161545 627 0.39 11771 48 0.41 7.29 18187.52 1325.24 1 in 55
Illinois 122848 1614 1.33 5525 113 2.09 4.50 9694.58 436.01 1 in 103
California 117215 2482 2.16 4305 88 2.09 3.67 2966.55 108.95 1 in 337
Massachusetts 101163 358 0.36 7085 50 0.71 7.00 14556.87 1019.50 1 in 69
Pennsylvania 77225 579 0.76 5667 100 1.80 7.34 6032.27 442.67 1 in 166
Texas 67310 1717 2.62 1716 33 1.96 2.55 2321.36 59.18 1 in 431
Michigan 57731 199 0.35 5553 37 0.67 9.62 5780.70 556.03 1 in 173
Florida 57447 617 1.09 2530 70 2.85 4.40 2674.72 117.80 1 in 374
Maryland 54175 848 1.59 2597 45 1.76 4.79 8960.94 429.56 1 in 112
Georgia 48207 305 0.64 2102 8 0.38 4.36 4540.37 197.98 1 in 220
Virginia 46239 841 1.85 1407 15 1.08 3.04 5417.25 164.84 1 in 185
Connecticut 42979 239 0.56 3972 2 0.05 9.24 12054.85 1114.08 1 in 83
Louisiana 40746 405 1.00 2835 34 1.21 6.96 8764.85 609.84 1 in 114
Ohio 36350 366 1.02 2259 52 2.36 6.21 3109.73 193.26 1 in 322
Indiana 35237 407 1.17 2197 54 2.52 6.23 5234.08 326.34 1 in 191
North Carolina 30023 431 1.46 961 13 1.37 3.20 2862.58 91.63 1 in 349
Colorado 26774 211 0.79 1474 16 1.10 5.51 4649.28 255.96 1 in 215
Minnesota 25508 300 1.19 1082 22 2.08 4.24 4522.99 191.86 1 in 221
Tennessee 24342 1776 7.87 381 17 4.67 1.57 3562.33 55.76 1 in 281
Washington 22157 180 0.82 1129 6 0.53 5.10 2909.69 148.26 1 in 344
Arizona 21264 1135 5.64 943 25 2.72 4.43 2792.42 123.84 1 in 358
Iowa 20019 320 1.62 561 6 1.08 2.80 6345.03 177.81 1 in 158
Wisconsin 18917 374 2.02 607 12 2.02 3.21 3248.98 104.25 1 in 308
Alabama 18766 136 0.73 653 7 1.08 3.48 3827.31 133.18 1 in 261
Mississippi 16041 289 1.83 767 28 3.79 4.78 5389.85 257.72 1 in 186
Rhode Island 15112 121 0.81 732 12 1.67 4.84 14265.20 690.98 1 in 70
Nebraska 14616 271 1.89 170 0 0.00 1.16 7555.80 87.88 1 in 132
Missouri 14015 291 2.12 786 10 1.29 5.61 2283.53 128.07 1 in 438
South Carolina 12415 267 2.20 501 1 0.20 4.04 2411.28 97.31 1 in 415
Utah 10202 203 2.03 113 0 0.00 1.11 3182.20 35.25 1 in 314
Kentucky 10185 139 1.38 442 3 0.68 4.34 2279.71 98.93 1 in 439
Kansas 9965 45 0.45 222 5 2.30 2.23 3420.50 76.20 1 in 292
Delaware 9685 80 0.83 373 5 1.36 3.85 9945.94 383.05 1 in 101
District of Columbia 8886 29 0.33 470 2 0.43 5.29 12590.88 665.96 1 in 79
Nevada 8858 156 1.79 417 0 0.00 4.71 2875.83 135.38 1 in 348
New Mexico 8024 224 2.87 367 5 1.38 4.57 3826.73 175.03 1 in 261
Arkansas 7818 375 5.04 136 3 2.26 1.74 2590.61 45.07 1 in 386
Oklahoma 6692 119 1.81 339 5 1.50 5.07 1691.19 85.67 1 in 591
South Dakota 5067 33 0.66 62 0 0.00 1.22 5727.63 70.08 1 in 175
New Hampshire 4749 64 1.37 256 11 4.49 5.39 3492.65 188.28 1 in 286
Oregon 4335 33 0.77 157 3 1.95 3.62 1027.80 37.22 1 in 973
Puerto Rico 3935 62 1.60 138 2 1.47 3.51 1232.12 43.21 1 in 812
Idaho 2933 94 3.31 83 1 1.22 2.83 1636.66 46.32 1 in 611
North Dakota 2646 21 0.80 65 4 6.56 2.46 3472.16 85.29 1 in 288
Maine 2377 28 1.19 94 5 5.62 3.95 1768.32 69.93 1 in 566
West Virginia 2056 28 1.38 78 2 2.63 3.79 1150.44 43.64 1 in 869
Vermont 988 5 0.51 55 0 0.00 5.57 1583.36 88.14 1 in 632
Wyoming 912 2 0.22 17 0 0.00 1.86 1575.79 29.37 1 in 635
Hawaii 653 1 0.15 17 0 0.00 2.60 461.20 12.01 1 in 2168
Montana 523 4 0.77 17 0 0.00 3.25 489.34 15.91 1 in 2044
Alaska 486 20 4.29 10 0 0.00 2.06 664.35 13.67 1 in 1505

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 2167831 373040 17.21 111436.20
New Jersey 817677 161545 19.76 92058.04
Illinois 934704 122848 13.14 73762.41
California 2071591 117215 5.66 52429.12
Massachusetts 609395 101163 16.60 87689.00
Pennsylvania 472871 77225 16.33 36937.31
Texas 986224 67310 6.83 34012.56
Michigan 577268 57731 10.00 57802.77
Florida 1049752 57447 5.47 48876.29
Maryland 315815 54175 17.15 52238.13
Georgia 474287 48207 10.16 44670.63
Virginia 328889 46239 14.06 38531.81
Connecticut 270610 42979 15.88 75901.32
Louisiana 393133 40746 10.36 84566.66
Ohio 409908 36350 8.87 35067.54
Indiana 271919 35237 12.96 40390.69
North Carolina 434921 30023 6.90 41468.11
Colorado 190537 26774 14.05 33086.60
Minnesota 258747 25508 9.86 45880.12
Tennessee 462136 24342 5.27 67631.24
Washington 365272 22157 6.07 47968.11
Arizona 237833 21264 8.94 31232.61
Iowa 163690 20019 12.23 51881.57
Wisconsin 282660 18917 6.69 48546.71
Alabama 223802 18766 8.39 45644.21
Mississippi 179498 16041 8.94 60312.17
Rhode Island 159560 15112 9.47 150619.10
Nebraska 106418 14616 13.73 55013.21
Missouri 205430 14015 6.82 33471.68
South Carolina 218777 12415 5.67 42491.58
Utah 221791 10202 4.60 69180.88
Kentucky 227271 10185 4.48 50870.11
Kansas 103312 9965 9.65 35462.02
Delaware 64062 9685 15.12 65788.01
District of Columbia 47701 8886 18.63 67589.19
Nevada 152091 8858 5.82 49377.69
New Mexico 203115 8024 3.95 96867.70
Arkansas 133236 7818 5.87 44149.68
Oklahoma 204657 6692 3.27 51720.62
South Dakota 46846 5067 10.82 52953.74
New Hampshire 74344 4749 6.39 54676.32
Oregon 134209 4335 3.23 31820.14
Puerto Rico 3935 3935 100.00 1232.12
Idaho 48133 2933 6.09 26858.96
North Dakota 73644 2646 3.59 96637.81
Maine 52968 2377 4.49 39404.50
West Virginia 100543 2056 2.04 56258.94
Vermont 36619 988 2.70 58685.33
Wyoming 25742 912 3.54 44477.93
Hawaii 48921 653 1.33 34551.85
Montana 42212 523 1.24 39495.57
Alaska 56203 486 0.86 76827.81

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 72300 2287 3.27 31333 43.34 38502 2465 103 4.36 3.41
Tamil Nadu 24586 1091 4.64 13706 55.75 10680 200 13 6.95 0.81
Delhi 22132 1298 6.23 9243 41.76 12333 556 33 6.31 2.51
Gujarat 17632 415 2.41 11894 67.46 4646 1092 29 2.73 6.19
Rajasthan 9373 273 3.00 6435 68.65 2735 203 4 2.01 2.17
Uttar Pradesh 8729 368 4.40 5176 59.30 3324 229 7 3.15 2.62
Madhya Pradesh 8420 137 1.65 5221 62.01 2835 364 6 1.68 4.32
State Unassigned 7123 709 11.05 0 0.00 7123 0 0 NaN 0.00
West Bengal 6168 396 6.86 2410 39.07 3423 335 10 3.08 5.43
Bihar 4096 151 3.83 1803 44.02 2269 24 1 4.35 0.59
Karnataka 3796 388 11.38 1403 36.96 2339 52 0 0.00 1.37
Andhra Pradesh 3791 115 3.13 2414 63.68 1313 64 0 0.00 1.69
Telangana 2891 99 3.55 1526 52.78 1273 92 4 4.55 3.18
Jammu and Kashmir 2718 117 4.50 953 35.06 1732 33 2 6.45 1.21
Haryana 2652 296 12.56 1069 40.31 1560 23 2 9.52 0.87
Punjab 2342 41 1.78 2017 86.12 279 46 2 4.55 1.96
Odisha 2245 141 6.70 1325 59.02 911 9 0 0.00 0.40
Assam 1562 76 5.11 338 21.64 1217 4 0 0.00 0.26
Kerala 1413 86 6.48 627 44.37 774 12 1 9.09 0.85
Uttarakhand 1043 84 8.76 252 24.16 781 7 2 40.00 0.67
Jharkhand 722 61 9.23 296 41.00 421 5 0 0.00 0.69
Chhattisgarh 564 16 2.92 130 23.05 433 1 0 0.00 0.18
Tripura 471 48 11.35 173 36.73 298 0 0 NaN 0.00
Himachal Pradesh 345 5 1.47 136 39.42 200 6 0 0.00 1.74
Chandigarh 301 4 1.35 214 71.10 82 5 1 25.00 1.66
Manipur 89 6 7.23 14 15.73 75 0 0 NaN 0.00
Ladakh 81 4 5.19 47 58.02 33 1 1 Inf 1.23
Goa 79 6 8.22 57 72.15 22 0 0 NaN 0.00
Puducherry 79 0 0.00 25 31.65 54 0 0 NaN 0.00
Nagaland 58 15 34.88 0 0.00 58 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Meghalaya 30 2 7.14 12 40.00 17 1 0 0.00 3.33
Arunachal Pradesh 28 8 40.00 1 3.57 27 0 0 NaN 0.00
Mizoram 13 0 0.00 1 7.69 12 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 4 1 33.33 1 25.00 3 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 766122 89205 187 0.21 11.64 3021 166 20255 16143 18.10
Piemonte 325097 30715 57 0.19 9.45 849 46 4828 3884 12.65
Emilia-Romagna 333629 27828 19 0.07 8.34 358 50 2912 4136 14.86
Veneto 690267 19162 8 0.04 2.78 103 5 1403 1921 10.03
Toscana 257178 10117 10 0.10 3.93 85 25 1011 1053 10.41
Liguria 109060 9734 15 0.15 8.93 175 7 546 1468 15.08
Lazio 260102 7743 5 0.06 2.98 580 56 2847 741 9.57
Marche 104968 6734 4 0.06 6.42 60 9 1326 987 14.66
Campania 206834 4809 3 0.06 2.33 236 7 890 415 8.63
Puglia 121460 4498 0 0.00 3.70 134 11 1051 508 11.29
P.A. Trento 89787 4432 0 0.00 4.94 14 2 283 463 10.45
Sicilia 153417 3447 4 0.12 2.25 62 7 966 275 7.98
Friuli Venezia Giulia 136524 3276 2 0.06 2.40 40 2 244 336 10.26
Abruzzo 77892 3249 4 0.12 4.17 113 6 743 413 12.71
P.A. Bolzano 67643 2598 0 0.00 3.84 13 3 120 291 11.20
Umbria 71769 1431 0 0.00 1.99 15 2 31 76 5.31
Sardegna 58224 1357 0 0.00 2.33 21 1 155 131 9.65
Valle d’Aosta 15327 1187 0 0.00 7.74 10 0 13 143 12.05
Calabria 71617 1158 0 0.00 1.62 20 1 112 97 8.38
Molise 14951 436 0 0.00 2.92 3 2 133 22 5.05
Basilicata 30424 399 0 0.00 1.31 4 0 24 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 51593 239 0.47 4713 52 1.12 9.13 6042.98 552.02 1 in 165
Ontario 30259 414 1.39 2375 22 0.93 7.85 2056.78 161.43 1 in 486
Alberta 7057 13 0.18 143 0 0.00 2.03 1599.09 32.40 1 in 625
British Columbia 2601 4 0.15 165 0 0.00 6.34 508.91 32.28 1 in 1965
Nova Scotia 1057 0 0.00 60 0 0.00 5.68 1081.38 61.38 1 in 925
Saskatchewan 646 0 0.00 11 0 0.00 1.70 546.69 9.31 1 in 1829
Manitoba 297 2 0.68 7 0 0.00 2.36 215.61 5.08 1 in 4638
Newfoundland and Labrador 261 0 0.00 3 0 0.00 1.15 500.61 5.75 1 in 1998
New Brunswick 133 1 0.76 0 0 NaN 0.00 170.51 0.00 1 in 5865
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1597 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1093 4 0.37
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 792 7 0.88
Shanghai 673 7 1.04
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 577 3 0.52
Fujian 358 1 0.28
Hebei 328 6 1.83
Shaanxi 309 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 235 1 0.43
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5598.47 324.51 1 in 179
Brazil 2653.53 149.06 1 in 377
Russia 2928.62 34.82 1 in 341
United Kingdom 4205.18 593.80 1 in 238
Spain 5142.13 581.38 1 in 194
Italy 3861.03 554.40 1 in 259
India 154.74 4.35 1 in 6463
France 2813.11 432.05 1 in 355
Germany 2221.03 103.43 1 in 450
Peru 5285.64 144.05 1 in 189
Turkey 2048.69 56.74 1 in 488
Iran 1941.38 97.86 1 in 515
Chile 6021.39 65.82 1 in 166
Mexico 753.30 82.33 1 in 1327
Canada 2499.60 198.91 1 in 400
Saudi Arabia 2702.22 16.67 1 in 370
China 60.72 3.35 1 in 16468
Pakistan 387.81 8.23 1 in 2579
Qatar 22834.03 16.29 1 in 44
Belgium 5141.67 833.77 1 in 194

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 204377 21649 10.59
Cook Illinois 79673 3726 4.68
Los Angeles California 57219 2448 4.28
Nassau New York 40572 2127 5.24
Suffolk New York 39980 1909 4.77
Westchester New York 33633 1378 4.10
Philadelphia Pennsylvania 23034 1346 5.84
Middlesex Massachusetts 22296 1663 7.46
Wayne Michigan 20468 2475 12.09
Hudson New Jersey 18822 1188 6.31
Suffolk Massachusetts 18636 902 4.84
Bergen New Jersey 18333 1584 8.64
Miami-Dade Florida 18224 722 3.96
Essex New Jersey 17761 1672 9.41
Passaic New Jersey 16234 931 5.73
Middlesex New Jersey 16021 997 6.22
Union New Jersey 15868 1078 6.79
Fairfield Connecticut 15776 1287 8.16
Prince George’s Maryland 15553 552 3.55
Essex Massachusetts 14795 971 6.56
Rockland New York 13223 646 4.89
Harris Texas 13027 236 1.81
Montgomery Maryland 11731 624 5.32
New Haven Connecticut 11525 985 8.55
Worcester Massachusetts 11438 790 6.91
Fairfax Virginia 11426 391 3.42
Providence Rhode Island 11052 0 0.00
Dallas Texas 10719 245 2.29
Maricopa Arizona 10536 448 4.25
Hartford Connecticut 10536 1253 11.89
Orange New York 10449 444 4.25
Marion Indiana 9978 592 5.93
District of Columbia District of Columbia 8886 470 5.29
Ocean New Jersey 8817 743 8.43
Norfolk Massachusetts 8600 845 9.83
Hennepin Minnesota 8591 627 7.30
Lake Illinois 8450 307 3.63
Oakland Michigan 8412 999 11.88
Monmouth New Jersey 8289 608 7.34
Plymouth Massachusetts 8228 568 6.90
King Washington 8177 570 6.97
Riverside California 8155 342 4.19
Milwaukee Wisconsin 8004 309 3.86
DuPage Illinois 7818 380 4.86
Jefferson Louisiana 7711 453 5.87
San Diego California 7554 269 3.56
Bristol Massachusetts 7380 435 5.89
Broward Florida 7248 317 4.37
Montgomery Pennsylvania 7172 696 9.70
Orleans Louisiana 7156 506 7.07

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc